Use AI/ML technology in supporting Federal use cases.
Requirements
- 2-4 years industry experience developing ML/AI solutions and a passion for solving complex problems.
- 2-4 years industry experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, or scikit-learn.
- Strong programming skills in languages such as Python, R, or Java.
- Solid understanding of statistical methods, data structures, and algorithms.
- Experience with data preprocessing, feature engineering, and model evaluation techniques.
- Familiarity with big data technologies like Hadoop, Spark, or similar.
- Knowledge of cloud platforms such as AWS, Google Cloud, or Azure.
Responsibilities
- Collaborate with cross-functional teams to design and develop machine learning models and algorithms to address business needs.
- Analyze and process large datasets to extract meaningful insights and patterns.
- Collaborate with cross-functional teams to integrate machine learning solutions into existing systems and workflows.
- Optimize and fine-tune machine learning models for performance, scalability, and accuracy.
- Implement and maintain data pipelines to support machine learning workflows.
- Evaluate the effectiveness of machine learning models using appropriate metrics and validation techniques.
- Deploy machine learning models to production environments and monitor their performance.
Other
- Ability to hold a position of public trust with the US government.
- Excellent problem-solving skills and attention to detail.
- Strong communication skills and ability to work collaboratively in a team environment.
- Ability to manage multiple tasks and projects simultaneously while meeting deadlines.
- seasoned Machine Learning Engineer to work with our existing team of Data Scientists and Engineers to use AI/ML technology in supporting Federal use cases. We are looking for a more than just a "Machine Learning Engineer", but a technologist with excellent communication and customer service skills and a passion for data and problem solving.